Book similarity determination method, terminal and storage medium

Abstract

The present invention relates to a method, terminal, and storage medium for determining book similarity. The method comprises: obtaining a common user set of a first book and a second book to be processed and reading intensity information of each user in the common user set; pairing multiple users in the common user set to obtain multiple user pairs; determining a difference weight for each user pair based on the reading intensity information of each user in each user pair for the first book and the second book; determining the interest level of each user pair based on the reading intensity information of each user for the first book, the second book, and all books read; determining the product of the difference weight and the interest level of each user pair as the similarity of the user pair, and determining the sum of the similarities of multiple user pairs as the target similarity of the first book and the second book. The present invention improves the accuracy of determining similarities between different books.

Description

Technical Field

[0001] The present disclosure relates to the field of Internet technology, and in particular to a method for determining book similarity, a terminal, and a storage medium. Background Art

[0002] With the rapid development of Internet technology, electronic books are increasingly used and paid more attention to. Users can choose books of interest to read based on recommended books.

[0003] Currently, recommended books can be determined by the similarity between different books. However, the accuracy of determining the similarity between different books in related technologies is low, which leads to low accuracy of book recommendations and cannot meet the needs. Summary of the Invention

[0004] In order to solve the above technical problems, the present disclosure provides a method, a terminal and a storage medium for determining book similarity, so as to improve the accuracy of determining book similarity.

[0005] In a first aspect, an embodiment of the present disclosure provides a method for determining book similarity, comprising:

[0006] Obtaining a common user set of a first book and a second book to be processed and reading intensity information of each user in the common user set, wherein the common user set includes multiple users who have read the first book and the second book at the same time, and the reading intensity information of each user represents intensity information of each user for each book read;

[0007] Combining multiple users in the common user set in pairs to obtain multiple user pairs;

[0008] determining a difference weight for each user pair based on reading intensity information of each user in each user pair for the first book and the second book;

[0009] For each user pair, determining the interest level of each user pair based on the reading intensity information of each user for the first book, the second book, and all books that have been read;

[0010] The product of the difference weight and the interest level of each user pair is determined as the similarity of the user pair, and the sum of the similarities of the plurality of user pairs is determined as the target similarity between the first book and the second book.

[0011] In a second aspect, an embodiment of the present disclosure provides a terminal, including:

[0012] processor;

[0013] a memory for storing executable instructions;

[0014] The processor is configured to read executable instructions from the memory and execute the executable instructions to perform the following operations:

[0015] Obtaining a common user set of a first book and a second book to be processed and reading intensity information of each user in the common user set, wherein the common user set includes multiple users who have read the first book and the second book at the same time, and the reading intensity information of each user represents intensity information of each user for each book read;

[0016] Combining multiple users in the common user set in pairs to obtain multiple user pairs;

[0017] determining a difference weight for each user pair based on reading intensity information of each user in each user pair for the first book and the second book;

[0018] For each user pair, determining the interest level of each user pair based on the reading intensity information of each user for the first book, the second book, and all books that have been read;

[0019] The product of the difference weight and the interest level of each user pair is determined as the similarity of the user pair, and the sum of the similarities of the plurality of user pairs is determined as the target similarity between the first book and the second book.

[0020] In a third aspect, an embodiment of the present disclosure provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the processor implements the method for determining book similarity according to the first aspect.

[0021] One of the above technical solutions has the following advantages or beneficial effects:

[0022] According to the book similarity determination method, terminal and storage medium of the embodiment of the present disclosure, it is possible to obtain a common user set of the first book and the second book to be processed and the reading intensity information of each user in the common user set, wherein the common user set includes multiple users who have read the first book and the second book at the same time, and the reading intensity information of each user represents the intensity information of each user for each book read; the multiple users in the common user set are combined in pairs to obtain multiple user pairs; based on the reading intensity information of each user of each user pair for the first book and the second book, the difference weight of each user pair is determined; for each user pair, based on the reading intensity information of each user for the first book, the second book and all the books read, the interest of each user pair is determined; the product of the difference weight and the interest of each user pair is determined as the similarity of the user pair, and the sum of the similarities of multiple user pairs is determined as the target similarity of the first book and the second book. The disclosed embodiment uses the reading intensity information of multiple common users of two books to determine the product of the difference weight and interest level of each pair of user combinations as the corresponding similarity, and then the final similarity of the two books can be determined by the sum of the similarities of each pair of users. Since the similarity between each pair of users is determined by considering both the differences in different users' views on the two books and their interest levels, the considerations are more comprehensive, which improves the accuracy of determining the similarity between different books, and thus helps to improve the accuracy of subsequent book recommendations. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The above and other features, advantages, and aspects of the various embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and that the originals and elements are not necessarily drawn to scale.

[0024] Figure 1 A flowchart of a method for determining book similarity provided by an embodiment of the present disclosure;

[0025] Figure 2 A flowchart of another method for determining book similarity provided by an embodiment of the present disclosure;

[0026] Figure 3 A schematic diagram of a book recommendation provided by an embodiment of the present disclosure;

[0027] Figure 4 A schematic diagram of the structure of a terminal provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0028] The following describes embodiments of the present disclosure in more detail with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as limited to the embodiments described herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are for illustrative purposes only and are not intended to limit the scope of protection of the present disclosure.

[0029] It should be understood that the various steps described in the method embodiments of the present disclosure may be performed in different orders and / or in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present disclosure is not limited in this respect.

[0030] As used herein, the term "including" and its variations are open-ended, i.e., "including but not limited to." The term "based on" means "based, at least in part, on." The term "one embodiment" means "at least one embodiment," the term "another embodiment" means "at least one additional embodiment," and the term "some embodiments" means "at least some embodiments." Other terms are defined in the following description.

[0031] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0032] It should be noted that the modifications of "one" and "multiple" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, they should be understood as "one or more".

[0033] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0034] In order to solve the problem of low accuracy in determining the similarity of different books in related technologies, an embodiment of the present disclosure provides a method for determining book similarity, which is introduced below in conjunction with specific embodiments.

[0035] Figure 1 This is a flow chart of a method for determining book similarity provided by an embodiment of the present disclosure. This method can be executed by a device for determining book similarity, wherein the device can be implemented using software and / or hardware and can generally be integrated into a terminal or server. Figure 1 As shown, the method includes:

[0036] Step 101: Obtain a common user set of a first book and a second book to be processed and reading intensity information of each user in the common user set.

[0037] Among them, the first book and the second book can be any two books that need to determine the similarity. For example, the first book can be the current book that the user is reading, and the second book can be one of multiple books associated with the first book, such as the second book can be one of multiple books written by the same author as the first book. The common user set may include multiple users who have read the first book and the second book at the same time. The reading intensity information of each user represents the intensity information of each user for each book read, and may include the reading intensity information of each user for the first book and the second book respectively. Reading intensity information can be information that characterizes the user's reading depth and interest in a book. Reading intensity information may include one or more types of information. For example, reading intensity information may include the reading time, interaction data, and payment status of a book, etc. The specific information can be determined according to actual conditions.

[0038] In an embodiment of the present disclosure, a book similarity determination device can obtain a first book and a second book that currently need to determine similarity, then determine a first set of users who have read the first book and a second set of users who have read the second book, determine the intersection of the first user set and the second user set as a common user set; and obtain reading intensity information of each user in the common user set.

[0039] Step 102: Combine multiple users in the common user set into pairs to obtain multiple user pairs.

[0040] After obtaining the common user set, the book similarity determination device can arbitrarily combine the multiple users included in the set into any two combinations to obtain multiple user pairs. Each user pair can include any two users in the common user set, and there are no two completely identical user pairs.

[0041] Optionally, when the number of users in the common user set exceeds a threshold, multiple users can be sampled. Specifically, a preset number of users from the common user set are extracted and then paired to form multiple user pairs. The threshold and the preset number can be determined based on actual circumstances. For example, the threshold could be 100, and the preset number could be 10. This sampling approach can reduce the computational effort required to subsequently determine the similarity between two books, thereby improving the efficiency of similarity determination.

[0042] Step 103: Determine a difference weight for each user pair based on the reading intensity information of each user in each user pair for the first book and the second book.

[0043] The difference weight can be understood as the difference in reading intensity of the two users in each user pair for the first book and the second book, that is, the difference in interest.

[0044] In some embodiments, based on the reading intensity information of each user in each user pair for the first book and the second book, determining the difference weight of each user pair includes: for each user pair, determining a first difference value between the first user and the second book, and a second difference value between the second user and the first book and the second book; and determining the difference weight of the user pair by dividing the first difference value by the second difference value.

[0045] The first difference value is equal to the reading intensity information of the first user for the first book divided by the reading intensity information of the first user for the second book, and the second difference value is equal to the reading intensity information of the second user for the first book divided by the reading intensity information of the second user for the second book.

[0046] Specifically, for each user pair, the reading intensity information of the two users in the user pair for the first book and the second book is input into the difference weight formula to obtain the difference weight of the user pair. The difference weight formula can be expressed as:

[0047] w=(u_items[u][i] / u_items[u][j]) / (u_items[v][i] / u_items[v][j])=(u_items[u][i]*u_items[v][j]) / (u_items[u][j]*u_items[v][i]));

[0048] Among them, w represents the difference weight of the current user pair, i represents the first book, j represents the second book, u represents the first user in the current user pair, v represents the second user in the current user pair, u_items[u][i] represents the reading intensity information of the first user u on the first book i, u_items[u][j] represents the reading intensity information of the first user u on the second book j, u_items[u][i] / u_items[u][j] represents the above-mentioned first difference value, u_items[v][i] represents the reading intensity information of the second user v on the first book i, u_items[v][j] represents the reading intensity information of the second user v on the second book j, and u_items[v][i] / u_items[v][j] represents the above-mentioned second difference value.

[0049] The difference weight is greater than 0 and less than or equal to 1, that is, the difference weight is between 0 and 1. When the calculated difference weight is greater than 1, the inverse of the current difference weight can be taken as the final difference weight. For example, when a user's difference weight calculated according to the above formula is 2, the final difference weight of the user pair is 0.5.

[0050] Step 104 : For each user pair, determine the interest level of each user pair based on the reading intensity information of each user for the first book, the second book, and all the books that have been read.

[0051] The interest level can be understood as a user's interest level or preference level for the first book and the second book relative to all books read by the user. The interest level of a user pair can be the sum of the interest levels of the two users in the user pair.

[0052] In an embodiment of the present disclosure, for each user pair, the interest level of each user pair is determined based on the reading intensity information of each user for the first book, the second book, and all the books that have been read, including: for each user pair, respectively determining the first interest value of the first user for the first book and the second book, and the second interest value of the second user for the first book and the second book; and determining the sum of the first interest value and the second interest value as the interest level of the user pair.

[0053] The first interest value is equal to the sum of the first user's reading intensity information for the first book and the second book divided by the total reading intensity information of the first user for all books read; the second interest value is equal to the sum of the second user's reading intensity information for the first book and the second book divided by the total reading intensity information of the second user for all books read.

[0054] Specifically, for each user pair, the reading intensity information of the two users in the user pair on the above-mentioned first book and the second book, as well as the total reading intensity information on all the books read are input into the interest formula to obtain the interest of the user pair. The interest formula can be expressed as: t=t1+t2, where t1=(u_items[u][i]+u_items[u][j]) / sum(list(u_items[u].values()), t2=(u_items[v][i]+u_items[v][j]) / sum(list(u_items[v].values()). Where t represents the interest of the current user pair, t1 represents the first interest value, t2 represents the second interest value, i represents the first book, j represents the second book, u represents the first user in the current user pair, v represents the second user in the current user pair, u_items[u][i] represents the reading intensity information of the first user u on the first book i, and u_items[u][j] represents the reading intensity information of the first user u on the second book j. Reading intensity information, u_items[u][i]+u_items[u][j] represents the sum of the reading intensity information of the first user u for the first book i and the second book j, and sum(list(u_items[u].values())) represents the total reading intensity information of the first user u for all the books he has read; u_items[v][i] represents the reading intensity information of the first book i by user v, and u_items[v][j] represents the reading intensity information of the second book j by user v, and u_items[v][i]+u_items[v][j] represents the sum of the reading intensity information of the second user v for the first book i and the second book j, and sum(list(u_items[v].values())) represents the total reading intensity information of the second user v for all the books he has read.

[0055] That is, t=(u_items[u][i]+u_items[u][j]) / sum(list(u_items[u].values())+(u_items[v][i]+u_items[v][j]) / sum(list(u_items[v].values())).

[0056] Step 105: Determine the product of the difference weight and the interest level of each user pair as the similarity of the user pair, and determine the sum of the similarities of multiple user pairs as the target similarity between the first book and the second book.

[0057] The similarity between the user pair may be the similarity between the first book and the second book determined based on the current user pair, and the target similarity may be the similarity between the first book and the second book finally determined based on all user pairs.

[0058] Specifically, the target similarity between the first book and the second book can be determined by the following formula: result = S1 + S2 + ... + S n , result represents the target similarity between the first book and the second book, S i =w i *t i , where S i represents the similarity of the i-th user pair, i = 1, 2, 3…, n, n represents the number of user pairs obtained by pairwise combination in the above common user set, w i represents the difference weight of the i-th user pair, t i represents the interest of the i-th user in .

[0059] According to the book similarity determination method of the embodiment of the present disclosure, it is possible to obtain a common user set of the first book and the second book to be processed and the reading intensity information of each user in the common user set, wherein the common user set includes multiple users who have read the first book and the second book at the same time, and the reading intensity information of each user represents the intensity information of each user for each book read; the multiple users in the common user set are combined in pairs to obtain multiple user pairs; based on the reading intensity information of each user of each user pair for the first book and the second book, the difference weight of each user pair is determined; for each user pair, based on the reading intensity information of each user for the first book, the second book and all the books read, the interest of each user pair is determined; the product of the difference weight and the interest of each user pair is determined as the similarity of the user pair, and the sum of the similarities of multiple user pairs is determined as the target similarity of the first book and the second book. The disclosed embodiment uses the reading intensity information of multiple common users of two books to determine the product of the difference weight and interest level of each pair of user combinations as the corresponding similarity, and then the final similarity of the two books can be determined by the sum of the similarities of each pair of users. Since the similarity between each pair of users is determined by considering both the differences in different users' views on the two books and their interest levels, the considerations are more comprehensive, which improves the accuracy of determining the similarity between different books, and thus helps to improve the accuracy of subsequent book recommendations.

[0060] In some embodiments, the reading intensity information may include at least one of the following: reading time, number of interactions, reading level, number of payments, payment amount and attenuation value of reading time. The number of interactions includes at least one of the number of likes, comments and shares. The reading level is determined based on the reading time, the time difference between the reading time and the current time and the attenuation value.

[0061] Reading time can be the sum of the time a user spends reading a book at different times. Reading level can be understood as the depth of a user's reading of a book, which can be determined based on reading time, the time difference between the reading time and the current time, the decay value, and the reading level formula. The reading level formula can be expressed as x = t*a y , where x represents the reading level of a single reading, t represents the reading time, a represents the decay value, which can be a fixed value, for example, the decay value can be set to 0.95, and y represents the time difference between the reading time and the current time. For example, if the current user read a book for 3 hours 50 days ago and the decay value is set to 0.95, then the reading level x = 3*0.95 50 , which means 3 times 0.95 raised to the power of 50. The reading level can be the sum of the unit reading levels of a book read by a user multiple times. That is, the reading level of a user for the book can be obtained by adding up the unit reading levels of multiple readings.

[0062] The number of payments and the payment amount may be representations related to payment, and the reading intensity information may be the sum of the number of payments made by the user for a book, or the sum of the amounts paid by the user for a book.

[0063] The decay value of reading time can be the decay value corresponding to the user's most recent reading time of a book. The decay value can be inversely proportional to the reading time. The earlier the reading time, the smaller the decay value. For example, if the reading time is from the current time to one month ago, the decay value is 0.95; if the reading time is from one month to one year ago, the decay value is 0.5; and if the reading time is any time before one year ago, the decay value is 0.1. The above are just examples. The decay value can also change according to a certain pattern, for example, the decay value can change in a linear, broken line, or exponential manner.

[0064] The reading intensity information in the embodiments of the present disclosure can be represented by various types of information, which improves the richness and diversity of the reading intensity information and facilitates subsequent book recommendations.

[0065] For example, Figure 2 A flow chart of another method for determining book similarity provided by an embodiment of the present disclosure is shown as follows: Figure 2As shown, in a feasible implementation, when the first book is the current book being read by the user, after determining the sum of the similarities between multiple user pairs as the target similarity between the first book and the second book, the solution may further include:

[0066] Step 201 : Determine whether the target similarity is greater than or equal to a similarity threshold. If so, execute step 202 ; otherwise, execute step 203 .

[0067] The similarity threshold can be set according to actual conditions.

[0068] After determining the target similarity between the first book and the second book, the target similarity may be compared with a similarity threshold. If the target similarity is greater than or equal to the similarity threshold, step 202 may be executed; otherwise, step 203 may be executed.

[0069] Step 202: Determine the second book as a recommended book and recommend it to the user.

[0070] The recommended books may be the books that are finally recommended to the current user. Since the first book is the current book that the user is reading, the recommended books may be determined based on the first book and recommended books may be recommended. Specifically, the recommendation may be implemented by displaying recommendation information including the recommended books.

[0071] For example, Figure 3 A schematic diagram of a book recommendation provided by an embodiment of the present disclosure, such as Figure 3 As shown in the figure, a display page 300 of a first book A is shown. The first book A is the current book that the user is reading, and the recommended book determined for the first book A is the second book B. The display page 300 can display recommendation information 301 including the second book B. The recommendation information 301 may include information such as the name and cover of the second book B, which is used to prompt the user to read the second book B related to the first book A.

[0072] above Figure 3 This corresponds to the recommendation scenario where the first book is the current book. Figure 3 The recommendation methods in the following are only examples, and other methods of recommending books are applicable.

[0073] Step 203: re-determine a new second book, and return to determine the target similarity between the first book and the new second book.

[0074] When it is determined that the target similarity is less than the aforementioned similarity threshold, a new second book may be newly determined from multiple books associated with the first book. The multiple books associated with the first book may be books that share at least one attribute information with the first book. The attribute information may include information such as book type, writing time, and author. Then, step 101 may be performed to determine the target similarity between the first book and the new second book. The target similarity is then compared with the similarity threshold to determine whether to recommend the new second book. This continues until the number of recommended books reaches a preset number, which can be set based on actual circumstances, for example, 5.

[0075] Optionally, there may be multiple second books. After determining the target similarity between each second book and the first book, books with target similarity greater than or equal to the similarity threshold among the multiple second books are determined as recommended books and recommended to the user.

[0076] In the above scheme, by adopting the more accurate similarity determination method of this embodiment, when determining recommended books, books that the user is more interested in can be screened out for recommendation, thereby improving the accuracy of book recommendations and further improving the user's reading stickiness and interest.

[0077] The present disclosure also provides a terminal, which may include a processor and a memory, and the memory may be used to store executable instructions. The processor may be used to read the executable instructions from the memory and execute the executable instructions to perform the following operations: obtain a common user set of the first book and the second book to be processed and the reading intensity information of each user in the common user set, wherein the common user set includes multiple users who have read the first book and the second book at the same time, and the reading intensity information of each user represents the intensity information of each user for each book read; combine multiple users in the common user set in pairs to obtain multiple user pairs; determine the difference weight of each user pair based on the reading intensity information of each user in each user pair for the first book and the second book; for each user pair, determine the interest of each user pair based on the reading intensity information of each user for the first book, the second book, and all the books read; determine the product of the difference weight and the interest of each user pair as the similarity of the user pair, and determine the sum of the similarities of multiple user pairs as the target similarity of the first book and the second book.

[0078] Figure 4 This is a schematic diagram of the structure of a terminal provided in an embodiment of the present disclosure. The terminal 400 in the embodiment of the present invention may be the electronic device described above. It should also be noted that: Figure 4 The terminal 400 shown is only an example and should not limit the functions and scope of use of the embodiments of the present invention.

[0079] The terminal 400 conventionally includes a processor 410 and a computer program product or computer-readable medium in the form of a memory 420. The memory 420 can be an electronic memory such as a flash memory, an EEPROM (Electrically Erasable Programmable Read-Only Memory), an EPROM, a hard disk or a ROM. The memory 420 has a storage space 421 for executable instructions (or program codes) 4211 for executing any method steps in the above-mentioned book similarity determination method. For example, the storage space 421 for executable instructions may include individual executable instructions 4211 for respectively implementing various steps in the above-mentioned book similarity determination method. These executable instructions can be read from or written to one or more computer program products. These computer program products include program code carriers such as a hard disk, a compact disc (CD), a memory card or a floppy disk. Such a computer program product is typically a portable or fixed storage unit. The storage unit may have a Figure 4 The memory 420 in the terminal is similarly arranged as a storage segment or storage space. The executable instructions can be compressed, for example, in an appropriate form. Generally, the storage unit includes executable instructions for executing the steps of the method for determining book similarity according to the present invention, i.e., codes that can be read by a processor such as processor 410. When executed by the terminal, these codes cause the terminal to execute the various steps of the method for determining book similarity described above.

[0080] An embodiment of the present invention further provides a computer-readable storage medium having computer program instructions stored thereon. When the computer program instructions are executed by a processor, the processor executes the book similarity determination method provided by each embodiment of the present invention.

[0081] The computer readable storage medium can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can, for example, include but is not limited to a system, device or component of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination thereof. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0082] The computer-readable medium may be included in the terminal, or may exist independently without being incorporated into the terminal.

[0083] In embodiments of the present invention, computer program code for performing the operations of the present invention may be written in one or more programming languages, or a combination thereof, including, but not limited to, object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0084] The various component embodiments of the present invention may be implemented in hardware in whole or in part, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that a microprocessor or digital signal processor (DSP) may be used in practice to implement some or all of the functions of some or all of the components of the book similarity determination apparatus according to an embodiment of the present invention. The present invention may also be implemented as a device or apparatus program (e.g., a computer program and a computer program product) for executing part or all of the methods described herein. Such a program for implementing the present invention may be stored on a computer-readable medium, or may be in the form of one or more signals. Such a signal may be downloaded from an Internet website, or provided on a carrier signal, or provided in any other form.

[0085] a1. According to one or more embodiments of the present disclosure, the present disclosure provides a method for determining book similarity, comprising:

[0086] Obtaining a common user set of a first book and a second book to be processed and reading intensity information of each user in the common user set, wherein the common user set includes multiple users who have read the first book and the second book at the same time, and the reading intensity information of each user represents intensity information of each user for each book read;

[0087] Combining multiple users in the common user set in pairs to obtain multiple user pairs;

[0088] determining a difference weight for each user pair based on reading intensity information of each user in each user pair for the first book and the second book;

[0089] For each user pair, determining the interest level of each user pair based on the reading intensity information of each user for the first book, the second book, and all books that have been read;

[0090] The product of the difference weight and the interest level of each user pair is determined as the similarity of the user pair, and the sum of the similarities of the plurality of user pairs is determined as the target similarity between the first book and the second book.

[0091] a2. The method according to a1, wherein determining the difference weight of each user pair based on the reading intensity information of each user in each user pair for the first book and the second book comprises:

[0092] For each user pair, determining a first difference value between the first user and the second book, and a second difference value between the second user and the first book;

[0093] A value obtained by dividing the first difference value by the second difference value is determined as a difference weight of the user pair, wherein the difference weight is greater than 0 and less than or equal to 1.

[0094] a3. The method according to a2, wherein the first difference value is equal to the reading intensity information of the first user for the first book divided by the reading intensity information of the first user for the second book, and the second difference value is equal to the reading intensity information of the second user for the first book divided by the reading intensity information of the second user for the second book.

[0095] a4. The method according to a1, wherein, for each user pair, determining the interest level of each user pair based on the reading intensity information of each user for the first book, the second book, and all books read comprises:

[0096] For each of the user pairs, determining a first interest value of the first user in the first book and the second book, and a second interest value of the second user in the first book and the second book;

[0097] The sum of the first interest value and the second interest value is determined as the interest level of the user pair.

[0098] a5. The method according to a4, wherein the first interest value is equal to the sum of the first user's reading intensity information for the first book and the second book divided by the value of the total reading intensity information of the first user for all books read, and the second interest value is equal to the sum of the second user's reading intensity information for the first book and the second book divided by the value of the total reading intensity information of the second user for all books read.

[0099] a6. The method according to a1, wherein, when the first book is the current book being read by the user, after determining the sum of the similarities of the multiple user pairs as the target similarity between the first book and the second book, the method further comprises:

[0100] When the target similarity is greater than or equal to a similarity threshold, the second book is determined as a recommended book and recommended to the user.

[0101] a7. The method according to any one of a1-a6, wherein the reading intensity information includes at least one of the following: reading time, number of interactions, reading level, number of payments, payment amount and attenuation value of reading time, the number of interactions includes at least one of the number of likes, number of comments and number of shares, and the reading level is determined based on the reading time, the time difference between the reading time and the current time and the attenuation value.

[0102] a8. According to one or more embodiments of the present disclosure, the present disclosure provides a terminal, comprising:

[0103] processor;

[0104] a memory for storing executable instructions;

[0105] The processor is configured to read the executable instructions from the memory and execute the executable instructions to perform the following operations:

[0106] Obtaining a common user set of a first book and a second book to be processed and reading intensity information of each user in the common user set, wherein the common user set includes multiple users who have read the first book and the second book at the same time, and the reading intensity information of each user represents intensity information of each user for each book read;

[0107] Combining multiple users in the common user set in pairs to obtain multiple user pairs;

[0108] determining a difference weight for each user pair based on reading intensity information of each user in each user pair for the first book and the second book;

[0109] For each user pair, determining the interest level of each user pair based on the reading intensity information of each user for the first book, the second book, and all books that have been read;

[0110] The product of the difference weight and the interest level of each user pair is determined as the similarity of the user pair, and the sum of the similarities of the plurality of user pairs is determined as the target similarity between the first book and the second book.

[0111] a9. The terminal according to a8, wherein the executable instruction further causes the processor to perform the following operations:

[0112] Determining the difference weight of each user pair based on the reading intensity information of each user in each user pair for the first book and the second book includes:

[0113] For each user pair, determining a first difference value between the first user and the second book, and a second difference value between the second user and the first book;

[0114] A value obtained by dividing the first difference value by the second difference value is determined as a difference weight of the user pair, wherein the difference weight is greater than 0 and less than or equal to 1.

[0115] a10. The terminal according to a9, wherein the first difference value is equal to the reading intensity information of the first user for the first book divided by the reading intensity information of the first user for the second book, and the second difference value is equal to the reading intensity information of the second user for the first book divided by the reading intensity information of the second user for the second book.

[0116] a11. The terminal according to a8, wherein the executable instruction further causes the processor to perform the following operations:

[0117] For each user pair, determining the interest level of each user pair based on the reading intensity information of each user for the first book, the second book, and all books that have been read includes:

[0118] For each of the user pairs, determining a first interest value of the first user in the first book and the second book, and a second interest value of the second user in the first book and the second book;

[0119] The sum of the first interest value and the second interest value is determined as the interest level of the user pair.

[0120] a12. A terminal according to a11, wherein the first interest value is equal to the sum of the first user's reading intensity information for the first book and the second book divided by the value of the first user's total reading intensity information for all books read, and the second interest value is equal to the sum of the second user's reading intensity information for the first book and the second book divided by the value of the second user's total reading intensity information for all books read.

[0121] a13. The terminal according to a8, wherein, when the first book is a current book being read by the user, after determining the sum of the similarities of the multiple user pairs as the target similarity between the first book and the second book, the executable instructions further cause the processor to perform the following operations:

[0122] When the target similarity is greater than or equal to a similarity threshold, the second book is determined as a recommended book and recommended to the user.

[0123] a14. A terminal according to any one of a9-13, wherein the reading intensity information includes at least one of the following: reading time, number of interactions, reading level, number of payments, payment amount and attenuation value of reading time, the number of interactions includes at least one of the number of likes, number of comments and number of shares, and the reading level is determined based on the reading time, the time difference between the reading time and the current time and the attenuation value.

[0124] a15. According to one or more embodiments of the present disclosure, the present disclosure provides a computer-readable storage medium, wherein the storage medium stores a computer program, and the computer program is used to execute any of the book similarity determination methods provided in the present disclosure.

[0125] The above description is merely a preferred embodiment of the present invention and an illustration of the technical principles employed. Those skilled in the art should understand that the scope of disclosure involved in the present invention is not limited to the technical solutions formed by the specific combination of the above-mentioned technical features, but also includes other technical solutions formed by any combination of the above-mentioned technical features or their equivalents without departing from the above-mentioned disclosed concepts. For example, a technical solution formed by replacing the above-mentioned features with (but not limited to) technical features with similar functions disclosed in the present invention.

[0126] In addition, although adopting specific order to describe each operation, this should not be interpreted as requiring these operations to be executed in the specific order shown or in sequential order.Under certain environment, multitasking and parallel processing may be advantageous.Similarly, although comprising some specific implementation details in the above discussion, these should not be interpreted as limiting the scope of the present invention.Some features described in the context of independent embodiment can also be implemented in single embodiment in combination.On the contrary, the various features described in the context of independent embodiment also can be implemented in multiple embodiments individually or in the mode of any suitable subcombination.

[0127] Although the subject matter has been described in language specific to structural features and / or methodological logical acts, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are merely example forms of implementing the claims.

Claims

1. A method for determining book similarity, characterized in that: include: Obtaining a common user set of a first book and a second book to be processed and reading intensity information of each user in the common user set, wherein the common user set includes multiple users who have read the first book and the second book at the same time, and the reading intensity information of each user represents intensity information of each user for each book read; Combining multiple users in the common user set in pairs to obtain multiple user pairs; determining a difference weight for each user pair based on reading intensity information of each user in each user pair for the first book and the second book; For each user pair, determining the interest level of each user pair based on the reading intensity information of each user for the first book, the second book, and all books that have been read; determining a product of the difference weight and the interest degree of each user pair as the similarity of the user pair, and determining a sum of the similarities of the plurality of user pairs as a target similarity between the first book and the second book; Determining a difference weight for each user pair based on reading intensity information of each user in each user pair for the first book and the second book includes: For each user pair, determining a first difference value between the first user and the second book, and a second difference value between the second user and the first book; determining a value obtained by dividing the first difference value by the second difference value as a difference weight of the user pair, wherein the difference weight is greater than 0 and less than or equal to 1; When the first book is the current book being read by the user, after determining the sum of the similarities of the plurality of user pairs as the target similarity between the first book and the second book, the method further includes: When the target similarity is greater than or equal to a similarity threshold, the second book is determined as a recommended book and recommended to the user; When the target similarity is less than the similarity threshold, a new second book is re-determined, and the target similarity between the first book and the new second book is returned to be determined; The re-determination of a new second book includes: A new second book is newly determined from a plurality of books associated with the first book, wherein the plurality of books associated with the first book are books having at least one attribute information identical to that of the first book.

2. The method according to claim 1, characterized in that The first difference value is equal to the reading intensity information of the first user for the first book divided by the reading intensity information of the first user for the second book, and the second difference value is equal to the reading intensity information of the second user for the first book divided by the reading intensity information of the second user for the second book.

3. The method according to claim 1, characterized in that For each user pair, determining the interest level of each user pair based on the reading intensity information of each user for the first book, the second book, and all books that have been read includes: For each of the user pairs, determining a first interest value of the first user in the first book and the second book, and a second interest value of the second user in the first book and the second book; The sum of the first interest value and the second interest value is determined as the interest level of the user pair.

4. The method according to claim 3, characterized in that The first interest value is equal to the sum of the first user's reading intensity information for the first book and the second book divided by the total reading intensity information of the first user for all books read, and the second interest value is equal to the sum of the second user's reading intensity information for the first book and the second book divided by the total reading intensity information of the second user for all books read.

5. The method according to any one of claims 1 to 4, characterized in that: The reading intensity information includes at least one of the following: reading time, number of interactions, reading level, number of payments, payment amount and attenuation value of reading time. The number of interactions includes at least one of the number of likes, comments and shares. The reading level is determined based on the reading time, the time difference between the reading time and the current time and the attenuation value.

6. A terminal, characterized in that: include: processor; a memory for storing executable instructions; The processor is configured to read the executable instructions from the memory and execute the executable instructions to perform the following operations: Obtaining a common user set of a first book and a second book to be processed and reading intensity information of each user in the common user set, wherein the common user set includes multiple users who have read the first book and the second book at the same time, and the reading intensity information of each user represents intensity information of each user for each book read; Combining multiple users in the common user set in pairs to obtain multiple user pairs; determining a difference weight for each user pair based on reading intensity information of each user in each user pair for the first book and the second book; For each user pair, determining the interest level of each user pair based on the reading intensity information of each user for the first book, the second book, and all books that have been read; determining a product of the difference weight and the interest degree of each user pair as the similarity of the user pair, and determining a sum of the similarities of the plurality of user pairs as a target similarity between the first book and the second book; The executable instructions further cause the processor to: Determining the difference weight of each user pair based on the reading intensity information of each user in each user pair for the first book and the second book includes: For each user pair, determining a first difference value between the first user and the second book, and a second difference value between the second user and the first book; determining a value obtained by dividing the first difference value by the second difference value as a difference weight of the user pair, wherein the difference weight is greater than 0 and less than or equal to 1; When the first book is the current book being read by the user, after determining the sum of the similarities of the multiple user pairs as the target similarity between the first book and the second book, the executable instructions further cause the processor to perform the following operations: When the target similarity is greater than or equal to a similarity threshold, the second book is determined as a recommended book and recommended to the user; When the target similarity is less than the similarity threshold, a new second book is re-determined, and the target similarity between the first book and the new second book is returned to be determined; The re-determination of a new second book includes: A new second book is newly determined from a plurality of books associated with the first book, wherein the plurality of books associated with the first book are books having at least one attribute information identical to that of the first book.

7. The terminal according to claim 6, characterized in that The first difference value is equal to the reading intensity information of the first user for the first book divided by the reading intensity information of the first user for the second book, and the second difference value is equal to the reading intensity information of the second user for the first book divided by the reading intensity information of the second user for the second book. The terminal according to claim 6, wherein: The executable instructions further cause the processor to: For each user pair, determining the interest level of each user pair based on the reading intensity information of each user for the first book, the second book, and all books that have been read includes: For each of the user pairs, determining a first interest value of the first user in the first book and the second book, and a second interest value of the second user in the first book and the second book; The sum of the first interest value and the second interest value is determined as the interest level of the user pair.

9. The terminal according to claim 8, characterized in that The first interest value is equal to the sum of the first user's reading intensity information for the first book and the second book divided by the total reading intensity information of the first user for all books read, and the second interest value is equal to the sum of the second user's reading intensity information for the first book and the second book divided by the total reading intensity information of the second user for all books read.

10. The terminal according to any one of claims 6 to 9, characterized in that: The reading intensity information includes at least one of the following: reading time, number of interactions, reading level, number of payments, payment amount and attenuation value of reading time. The number of interactions includes at least one of the number of likes, comments and shares. The reading level is determined based on the reading time, the time difference between the reading time and the current time and the attenuation value.

11. A computer-readable storage medium, characterized in that The storage medium stores a computer program, and when the computer program is executed by a processor, the processor implements the method for determining book similarity according to any one of claims 1 to 5.

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